Appendix: Theoretical effects of segregation distortion on performance of
interval mapping. Evidence of segregation distortion in this data set and the
knowledge that segregation distortion can arise from factors other than linkage to a
selected gene motivated further analyses. This was driven mainly by the inclusion of
markers from the X chromosome for which segregation distortion could naturally
arise, depending on the proximity of the markers to the true X (non-pseudoautosomal) region of the chromosome. It is suggested by CHURCHILL and DOERGE
(1994) that thresholds set by permutation testing will account for segregation
distortion in the data, however, we are not aware of any study that has confirmed this.
Simulations were therefore carried out to assess the effects of non-disease-related,
sex-chromosome-based segregation distortion on interval mapping using this type of
data set (half-sib families of all daughters with only sire and daughter genotypes
available). The specific details were based on the genotype data for the four pseudoautosomal X markers in this study, one of which was assumed to be tightly linked to
the non-autosomal portion of the X chromosome.
We simulated a population of individuals based on the data from this study: four sires,
50 dams per sire and 50 genotyped daughters (one per dam). Marker genotypes for
the sires were modified from the actual data so that sires were informative for all loci,
genotypes of the dams were simulated using the allele frequencies measured in the
data set and genotypes for the daughters were based on random union of sire and dam
gametes, allowing recombination according to the map distances calculated above
using Crimap. In addition, genotypes were generated for a fictitious X-linked marker
with five alleles, assumed to have a map distance of 0.05 centimorgans from the most
centromeric of the four actual markers. Phenotypes for each offspring were assigned
as either "0" or "1" with equal probability so that there was no association between
genotype and phenotype.
Phenotypes and genotypes for the four pseudo-automosomal markers of the four sires
and the 200 daughters (4 sires x 50 daughters each) were analysed using QTL Express
as described for the actual data. Significance of the computed F-ratio at the p<0.05
level was determined by permutation tests (1000 permutations). This process was
repeated for 50 independent simulated data sets.
Out of the 50 simulated datasets, 2 significant associations (4%) were found, within
the expected 5% rate of false positives. From this we conclude that there is no
tendency for segregation distortion to increase the rate of false positives detected by
interval mapping.